mcmodels.models.voxel.VoxelConnectivityArray¶
-
class
mcmodels.models.voxel.
VoxelConnectivityArray
(weights, nodes)[source]¶ Class for implicit construction of the voxel model.
VoxelConnectivityArray is used to perfom analysis on the large (~200,000 by 400,000 element) voxel-scale connectivity matrix on normal* machines (loading the entire matrix would take hundreds of GB of working memory). You can access elements of the VoxelConnectivityArray object just like a list or numpy array, where each call to __getitem__ will implicitly construct the given slice of the array. Additionally, several numpy.ndarray methods have been implemented.
See
VoxelModel
for weights/nodes descriptions.Parameters: - weights : array-like, shape (n_voxels, n_exps)
Weights matrix from fitted VoxelModel.
- nodes : array-like, shape (n_exps, n_voxels)
Nodes matrix from fitted VoxelModel.
Examples
>>> from mcmodels.core import VoxelModelCache >>> cache = VoxelModelCache() >>> voxel_array, source_mask, target_mask = cache.get_voxel_connectivity_array() >>> # VoxelConnectivityArray has several numpy.ndarray like methods >>> # get some arbitrary model weights >>> voxel_array[20:22, 10123] array([0.000145, 0.000098]) >>> voxel_array.shape (226346, 448962) >>> voxel_array.T VoxelConnectivityArray(dtype=float32, shape=(448962, 226346))
Attributes: Methods
astype
(self, dtype, \*\*kwargs)Consistent with numpy.ndarray.astype. from_csv
(weights_file, nodes_file, \*\*kwargs)Alternative constructor loading weights, nodes from .csv files. from_fitted_voxel_model
(voxel_model)Alternative constructor using fitted VoxelModel
object.from_npy
(weights_file, nodes_file, \*\*kwargs)Alternative constructor loading weights, nodes from npy, npz files. itercolumns
(self)Generator for yielding columns of the voxel matrix. itercolumns_blocked
(self[, n_blocks])Generator for yielding blocked columns of the voxel matrix. iterrows
(self)Generator for yielding rows of the voxel matrix. iterrows_blocked
(self, n_blocks)Generator for yielding blocked rows of the voxel matrix. mean
(self[, axis])Consistent with numpy.ndarray.mean. sum
(self[, axis])Consistent with numpy.ndarray.sum. transpose
(self)Returns transpose of full array. Methods
__init__
(self, weights, nodes)astype
(self, dtype, \*\*kwargs)Consistent with numpy.ndarray.astype. from_csv
(weights_file, nodes_file, \*\*kwargs)Alternative constructor loading weights, nodes from .csv files. from_fitted_voxel_model
(voxel_model)Alternative constructor using fitted VoxelModel
object.from_npy
(weights_file, nodes_file, \*\*kwargs)Alternative constructor loading weights, nodes from npy, npz files. itercolumns
(self)Generator for yielding columns of the voxel matrix. itercolumns_blocked
(self[, n_blocks])Generator for yielding blocked columns of the voxel matrix. iterrows
(self)Generator for yielding rows of the voxel matrix. iterrows_blocked
(self, n_blocks)Generator for yielding blocked rows of the voxel matrix. mean
(self[, axis])Consistent with numpy.ndarray.mean. sum
(self[, axis])Consistent with numpy.ndarray.sum. transpose
(self)Returns transpose of full array. -
T
¶ Short for transpose()
-
astype
(self, dtype, **kwargs)[source]¶ Consistent with numpy.ndarray.astype.
see numpy.ndarray.astype for more info.
Parameters: - dtype : string
Data type to convert array.
- **kwargs :
Keyword arguments to numpy.ndarray.astype
Returns: - self :
VoxelArray with new dtype.
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dtype
¶ numpy.dtype of full array
-
classmethod
from_csv
(weights_file, nodes_file, **kwargs)[source]¶ Alternative constructor loading weights, nodes from .csv files.
Parameters: - weights_file : string or path
Path to the .csv file containing the model weights. This file can have .gz or .bz2 compression
- nodes_file : string or path
Path to the .csv file containing the model nodes. This file can have .gz or .bz2 compression
- **kwargs
Optional keyword arguments supplied to numpy.loadtxt
Returns: - An instantiated VoxelConnectivityArray object.
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classmethod
from_fitted_voxel_model
(voxel_model)[source]¶ Alternative constructor using fitted
VoxelModel
object.Parameters: - voxel_model : A fitted
VoxelModel
object.
Returns: - An instantiated VoxelConnectivityArray object.
- voxel_model : A fitted
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classmethod
from_npy
(weights_file, nodes_file, **kwargs)[source]¶ Alternative constructor loading weights, nodes from npy, npz files.
Parameters: - weights_file : string or path
Path to the .npy or .npz file containing the model weights.
- nodes_file : string or path
Path to the .npy or .npz file containing the model nodes.
- **kwargs
Optional keyword arguments supplied to numpy.load
Returns: - An instantiated VoxelConnectivityArray object.
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itercolumns
(self)[source]¶ Generator for yielding columns of the voxel matrix.
Yields: - array : shape = (n_rows,)
Single column of the voxel-scale connectivity matrix.
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itercolumns_blocked
(self, n_blocks=0)[source]¶ Generator for yielding blocked columns of the voxel matrix.
Parameters: - n_blocks : int
The number of blocks of columns that is wished to be returned. Must be on the interval [1, n_columns].
Yields: - array : A block of columns of the full voxel-scale connectivity matrix.
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iterrows
(self)[source]¶ Generator for yielding rows of the voxel matrix.
Yields: - array : shape = (n_columns,)
Single row of the voxel-scale connectivity matrix.
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iterrows_blocked
(self, n_blocks)[source]¶ Generator for yielding blocked rows of the voxel matrix.
Parameters: - n_blocks : int
The number of blocks of rows that is wished to be returned. Must be on the interval [1, n_rows]
Yields: - array : A block of rows of the full voxel-scale connectivity matrix.
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mean
(self, axis=None)[source]¶ Consistent with numpy.ndarray.mean.
see numpy.ndarray.mean for more info.
Parameters: - axis - None, int, optional (default=None)
Axis over which to take mean.
Returns: - array
Mean along axis.
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shape
¶ numpy.shape of full array
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size
¶ numpy.size of full array
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sum
(self, axis=None)[source]¶ Consistent with numpy.ndarray.sum.
see numpy.ndarray.sum for more info.
Parameters: - axis - None, int, optional (default=None)
Axis over which to sum.
Returns: - array
Sum along axis.